the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Advancing N2O flux chamber measurement techniques in nutrient-poor ecosystems
Abstract. Nitrous oxide (N2O) is the third most important greenhouse gas, with its atmospheric concentration rising from 273 parts per billion (ppb) to 336 ppb since 1800, primarily due to agricultural activities. However, nutrient-poor natural soils, including those in the sub-Arctic, also emit and consume N2O. These soils have not been studied extensively, partly due to challenges in reliably detecting low fluxes. Methodological limitations were largely influenced by the available instrumentation; the lack of portable gas analysers for N2O with adequate accuracy led researchers to rely on manual air sampling from closed flux chambers, followed by laboratory analysis using gas chromatographs (GC). In this study, we utilized a fast-responding portable gas analyser (PGA; Aeris N2O/CO2) combined with a custom manual chamber system, which includes both transparent (light) and opaque (dark) measurements, to effectively measure low N2O fluxes from a nutrient-poor sub-Arctic peatland. We assessed the analyser's performance under low-flux conditions, evaluated the effects of chamber closure times, and compared linear and non-linear models for quantifying concentration gradients. Additionally, we analyzed flux rates based on high-frequency in situ observations against a method that randomly selects discrete samples from the full time series, simulating a GC-based approach. Our results indicate that the PGA can reliably detect and compute low N2O flux rates, averaging 12.9 ± 28.4 nmol m⁻² h⁻¹ under light conditions and -46.1 ± 38.2 nmol m⁻² h⁻¹ under dark conditions, depending on chamber closure time. The majority of fluxes (88 % for light and 74 % for dark measurements) exceeded the minimum detectable flux (MDF), which was 14.5 ± 1.05 nmol m⁻² h⁻¹ for light and 14.7 ± 1.08 nmol m⁻² h⁻¹ for dark measurements. Our comparison of chamber closure times (3–10 minutes) showed that a 3-minute closure may be inadequate for capturing low N2O fluxes during light measurements, while closure times of 4–10 minutes yield more reliable results. For dark measurements, where N2O uptake peaked with shorter closure times, we recommend a closure time of 3–5 minutes unless data are limited; in such cases, longer times may help capture fluxes above the MDF. In our study, all N2O fluxes were calculated using the non-linear model or corresponded with the linear model when data exhibited a linear distribution. Compared to PGA-based flux calculations, GC simulations underestimated N2O fluxes when using 3–6 samples. Therefore, we conclude that fast-responding analysers may be more suitable for measuring low N2O fluxes, enhancing our understanding of the complex dynamics of N2O emissions.
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Status: open (until 05 Mar 2025)
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RC1: 'Comment on amt-2024-203', Anonymous Referee #1, 24 Feb 2025
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Please find my comments in the attached document. I hope they are helpful for improving the manuscript
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RC2: 'Comment on amt-2024-203', Vytas Huth, 03 Mar 2025
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It is true that a lack of measurement precision so far prevents a sound in-situ assessment on the role of nutrient-poor ecosystems in N2O cycling and their potential to consume N2O. E.g. in Huth et al. (2022) Restoration Ecology, 30, e13490, we found a tendency of N2O uptake in Sphagnum-moss dominated plots, but due to the low precision of the GC sampling and measurements, we could not determine if that was actually significantly different from 0 or not. Therefore I much appreciate the efforts made by Triches et al. to test high-precision N2O measurements in a low-flux environment as this will substantially help elucidating the role of northern nutrient-poor ecosystems in global N2O cycling. The manuscript is generally well-written and fits nicely into the scope of the journal Atmospheric Measurement Techniques. I only had some minor comments and suggestions to make (especially in the discussion), except for the point that at very low N2O fluxes, CO2 uptake or efflux due to transparent or non-transparent chamber measurements could actually become a factor in either enriching or diluting N2O during closure time. Since I'm wondering if this may explain the differing results between the transparent and non-transparent chamber mesurements I would encourage the authors to use the Aeris CO2 data and check, if a correction similar to water vapor would change the results. If CO2 data is not available, I believe this should at least be thoroughly discussed.
Specific comments:
Abstract:
L.15-19: Please shortly mention your chamber height, because closure times are dependent on that.
Introduction:
L.33: Why not give credit to the early studies, e.g. Martikainen et al. (1993) Nature, 366, 51–53 or Nykänen et al. (1995) Journal of Biogeography, 22, 351–357.
L.34: If N availability is low, N2O uptake might be expected (Buchen et al. 2019, Soil Biology and Biochemistry, 130, 63-72) but up to now it was extremely hard to detect, e.g. via Helium incubation studies (ibid). The value of this study to me is that the role of (northern) nutrient-poor ecosystems in N2O cycling and potential uptake could now be elucidated.
L.61: Please add: "under a fixed chamber height", because closure times are directly depending on it (see Fiedler et al. 2022).
L.75: Was the chamber really dark? In general, the terms "light" and "dark" measurements can easily be misleading (e.g. our non-transparent chambers/our shading tarps are usually white to increase reflection and reduce chamber heating and I guess you did not really measure light, did you?), I would suggest you just use "transparent" and "non-transparent" (or "opaque") measurements/chambers etc. throughout the manuscript.
2 Methods
L.166: Does the Aeris analyser do not give dry mole fractions of the target gas? If so, shortly mention here or where you introduce the analyser.
3 Results and Discussion
L. 226: Does this warming period occur everytime once you turn on the analyser or was this first-use? Does this have implications for field application? I did not quite get if it is a problem, because at different RH, N2O concentration seems to be stable. Please just quickly inform the reader, if the analyser warm up may pose a problem or not.
L. 240: It's called atmospheric sign convention and this could be stated already in the methods under your flux calculation procedure.
L. 243-244: Complicated sentence and you already said in the methods, what a measurement period is. Please shorten and rephrase.
L.245ff: This is my major point that needs some attention and discussion: At low N2O concentration changes, CO2 concentration changes due to respiration (non-transparent measurents: N2O gets diluted, indicates uptake) or net uptake (transparent measurements: N2O gets enriched, indicates efflux) might become a factor. Either recalculate fluxes with a CO2 correction (like for water vapour), or add a short paragraph on this topic. If it is easily doable for you, you might also check in the lab, how realistic CO2 concentration changes affect N2O concentration and add it to the manuscript.
L314ff: Yes, but it also could just indicate CO2 saturation during closure time, hence a decrease in N2O dilution.
L317: It's not really due to fewer sampling points but rather due to the lower absolute change in concentration, that is below the one needed for flux detection see also Fiedler et al. (2022)
L320: It is not the chamber size, it's (effective) chamber height or V:A-ratio, that is determining concentration change and measurement length.
L321: Jungkunst et al. (2018) Journal of Plant Nutrition and Soil Science, 181, 7-11 actually assessed the trade off between reducing temporal accuracy of flux measurements to gain more spatial replicates. Might want to cite this here.
L336: What do you mean by LM and non-LM models exclude each other? The common approach is that if the difference between the two is non-significant, the simpler model should be used.
L343: Again, I don't understand this statement. If the data does not show non-linearity, linear models are sufficient. In any case, this statement should be rephrased, because I don't get how you assess that the relation between exponential and linear models do not appear to be recognised within the chamber community.
L350ff: That is true, but in theory, calculating fluxes from closed-chamber measurements actually assume non-disturbance conditions and non-linear models are a tool to calculate fluxes from disturbed measurements. Therefore it is also justifiable to reduce chamber closure time to the most linear part, because this signifies non-disturbance in your measurement. In other words, if concentration change is significantly different from linearity, chamber closure time was too long (or it wasn't properly sealed etc.).
L365ff: Does accuracy increase due to the fact that more GC samples better represent non-linearity of the data? Please discuss!
L.394: which = with?
4 Conclusion
Much of this is a repetition from previous paragraphs. Consider shortening and focusing on the main outcomes and recommendations.
Appendix
Figure A3: That's a really nice figure that I believe would be well-placed within the main text.
Citation: https://doi.org/10.5194/amt-2024-203-RC2
Model code and software
FluxProGenie- processing script Nathalie Triches, Jan Engel, and Abdullah Bolek https://git.bgc-jena.mpg.de/ntriches/data-analysis/-/tags/2024-12-12-triches-amtsubmission-n2oadvances
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